Olakunle Elijah;Abiodun Emmanuel Abioye;Tawanda E. Maguvu
{"title":"Pest and Disease Management in Ginger Plants: Artificial Intelligence of Things (AIoT)","authors":"Olakunle Elijah;Abiodun Emmanuel Abioye;Tawanda E. Maguvu","doi":"10.1109/TAFE.2024.3492323","DOIUrl":null,"url":null,"abstract":"Ginger (<italic>Zingiber officinale</i>), a globally cultivated spice crop, is vital to numerous economies. However, its production faces significant challenges due to pests and diseases, which can lead to substantial yield losses. Traditional methods for detecting these threats often rely on visual inspection by human experts, a process that is time-consuming, labor-intensive, and prone to errors. This article examines the potential of artificial intelligence (AI) to address these limitations and transform ginger cultivation. It provides a comprehensive analysis of conventional pest and disease management strategies, identifying their short comings and exploring the potential of emerging AI technologies, including the AI of things’ applications, for accurate, efficient, and timely detection and control. By pinpointing the challenges and outlining promising avenues for future research, this study aims to equip agriculturists and researchers with the knowledge necessary to optimize ginger production, enhance food security, and foster sustainable farming practices.","PeriodicalId":100637,"journal":{"name":"IEEE Transactions on AgriFood Electronics","volume":"3 1","pages":"86-97"},"PeriodicalIF":0.0000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on AgriFood Electronics","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10761055/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Ginger (Zingiber officinale), a globally cultivated spice crop, is vital to numerous economies. However, its production faces significant challenges due to pests and diseases, which can lead to substantial yield losses. Traditional methods for detecting these threats often rely on visual inspection by human experts, a process that is time-consuming, labor-intensive, and prone to errors. This article examines the potential of artificial intelligence (AI) to address these limitations and transform ginger cultivation. It provides a comprehensive analysis of conventional pest and disease management strategies, identifying their short comings and exploring the potential of emerging AI technologies, including the AI of things’ applications, for accurate, efficient, and timely detection and control. By pinpointing the challenges and outlining promising avenues for future research, this study aims to equip agriculturists and researchers with the knowledge necessary to optimize ginger production, enhance food security, and foster sustainable farming practices.